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Introducing an Early Warning System of Exchange Rate Volatility in Iranian Exchange Market: Markov Switching GARCH Method

Mohebalah Motahari (), Mohammad Reza Lotfali Pour () and Mohammad Taher Ahmadi Shadmehri ()
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Mohebalah Motahari: PhD Student of Economics, Ferdowsi University of Mashhad
Mohammad Reza Lotfali Pour: Professor of Economics, Ferdowsi University of Mashhad
Mohammad Taher Ahmadi Shadmehri: Associate Professor of Economics, Ferdowsi University of Mashhad

Quarterly Journal of Applied Theories of Economics, 2016, vol. 2, issue 4, pages 71-92

Abstract: Forecasting exchange rate volatility is important step in exchange market policy making to avoid high volatility of exchange rate. Exchange rate volatility is important because it is an index of investment uncertainty in each economy. The aim of this paper is introducing an Early Warning System (EWS) of high volatility of exchange rate in Iranian exchange market. Therefore, by estimation a Markov switching GARCH model, exchange rate volatility has been modeled. In this paper, the daily data of market exchange rate during 25thOrdibehesht 1385 until 21thTir 1394 has been used. With estimation of this model, transition matrix of probabilities of high and low volatility regimes has been calculated. By using this matrix, probabilities of high and low volatility regimes in Iranian Exchange Market have been calculated for future horizons so, it is possible to achieve a suitable model for forecasting high volatility of exchange rate regime in Iranian Exchange rate Market. The results of this system indicate that the probability of staying in high volatility exchange rate regime, the probability of transition from high to low volatility, the probability of transition from low to high volatility and the probability of staying in low volatility exchange rate regime are 0.14, 0.03, 0.86 and 0.97 respectively.

Keywords: Early Warning System; Exchange market volatility; Markov Switching GARCH (search for similar items in EconPapers)
JEL-codes: F30 F32 F37 (search for similar items in EconPapers)
Date: 2016
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